MACHINE LEARNING WITH CROSS OSI LAYER APPROACHES IN AUTONOMOUS FACTORY DEPLOYMENT FOR ULTRA-RELIABLE 6G MOBILE COMMUNICATIONS

6th Generation (6G) systems must support a diversified set of applications in a variety of situations, as described by 5G. Furthermore, as the smart sector grows, 6G will be able to satisfy the rising need for human-to-machine and machine-to-machine communications, particularly as robotics and autonomous vehicle/drone systems evolve. A huge number of heterogeneous data streams has created a massive computational complexity and thus, indirectly increases the end-to-end (E2E) latency, while decreasing reliability. Unfortunately, owing to various basic constraints in the design of the existing network architecture and communication protocols, today's communication falls short of meeting such demanding standards. This necessitates a rethinking nand redesigning of network design and protocols in order to effectively harness current technological breakthroughs in the future smart factory.